Rotation-invariant nonrigid point set matching in cluttered scenes

Wei Lian, Lei Zhang, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)

Abstract

This paper addresses the problem of rotation-invariant nonrigid point set matching. The shape context (SC) feature descriptor is used because of its strong discriminative nature, whereas edges in the graphs constructed by point sets are used to determine the orientations of SCs. Similar to lengths or directions, oriented SCs constructed this way can be regarded as attributes of edges. By matching edges between two point sets, rotation invariance is achieved. Two novel ways of constructing graphs on a model point set are proposed, aiming at making the orientations of SCs as robust to disturbances as possible. The structures of these graphs facilitate the use of dynamic programming (DP) for optimization. The strong discriminative nature of SC, the special structure of the model graphs, and the global optimality of DP make our methods robust to various types of disturbances, particularly clutters. The extensive experiments on both synthetic and real data validated the robustness of the proposed methods to various types of disturbances. They can robustly detect the desired shapes in complex and highly cluttered scenes.
Original languageEnglish
Article number6144738
Pages (from-to)2786-2797
Number of pages12
JournalIEEE Transactions on Image Processing
Volume21
Issue number5
DOIs
Publication statusPublished - 1 May 2012

Keywords

  • Dynamic programming (DP)
  • point set matching
  • shape context (SC)
  • shape representation

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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